Breaking Bad (Big Data)

Manufacturers are diving into Big Data to sharpen their decision-making. However, they are getting subpar results from being unable to break down the organizational silos that undermine their efforts to extract the most value out of their data.

Michael Rothschild, chairman of Profit Velocity Solutions, a San Francisco-based developer of performance improvement technologies, recently commented that implementation of enterprise systems has resulted in manufacturers accumulating “vast troves” of data. This data includes not only sensor readouts and machinery data but sales figures, transaction data, and logistics data, as well.

Silos are resulting in the creation of incompatible metrics and rendering the data useless. “Sales rely on margin per unit, while production looks at speed through the production process,” Rothschild wrote. “Genuine cooperation between sales, marketing, and the production side remains limited, which does not promote the overall interests of the business. They have not yet learned to take full advantage … to improve the competitiveness and profitability of their business.”

What needs to happen, he explained, is “a common set of operating data on which to make day-to-day decisions.” Jeff Carr, principal at Chicago-based Ultra Consultants, a research and consulting firm focused on enterprise resource planning systems, is seeing manufacturers struggling with the transformation of information into knowledge. Data, he said, must be employed for business insight.

“The challenge is not the size of the data, but how to organize and analyze the information to best drive performance improvements,” Carr told ThomasNet News.

In an interview, Rothschild said he thinks the key to breaking down organizational silos lies in the C-suite. It is up to management to look at Big Data from the big-picture standpoint of the shareholder, he said.

“As a manufacturer, yes, you make products and sell them, but you are really there to make money,” he said. “If Big Data and other aspects of the business are not being harnessed for the objective of making money, then something is awry. Big Data gives us the opportunity to create a more systematic, holistic approach.”

A recent study by research firm Aberdeen Group examined the adoption of Big Data technologies at 114 manufacturing companies. Researchers segmented those companies into “leaders” and “followers” based on four key performance indicators: successful new-product introductions, overall equipment effectiveness (OEE), on-time and complete shipments, and operating margin.

In the study, leaders recognized “the need to unlock hidden information” from the vast amount of collected data, for example, possible supply chain interruption from a supplier’s performance data. These high-performing companies regard this information the same way they see that downtime results from equipment age in their asset management data. Getting a handle on such hidden information requires analytics solutions. Seventy percent of respondent companies use dashboards and automatic reporting to this end, but “leaders are 25 percent more likely than followers to prioritize investments in interactive analytics to promote visual discovery,” Aberdeen noted in its report.

Carr of Ultra Consultants says such analytics are valuable. “The company has to look at the constant flow of data as it relates to the business,” he said.

He advises organizations to look for technology solutions and business information systems that can provide meaningful reports and insight in their key performance areas. “Reports, dashboards, performance data, and other reports should be easily shared with key team members” who have responsibility for seeing what the data means, he said. “Flexible reporting by user role is critical.”

The problem of organizational silos emerges as a significant theme in Aberdeen’s research. The study found, among respondents, wide recognition of the need to “help aggregate datasets across disparate functions to overcome data silos.” 

The higher-performing leaders in the study were more likely to support collaborations across functions to that end. Respondents by far (58 percent) identified the consolidation of the company’s enterprise data platform as the greatest business priority. The report advises that “[a] centralized data warehouse or master data management system helps [an organization] aggregate dispersed information.” Leaders are 34 percent more likely “to integrate data systems into a coherent environment to support decisions.”

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